Point cloud anomaly detection is steadily emerging as a promising research area.
Recognizing the importance of feature descriptiveness in this task, this study introduces the …

The technology of big data analysis and artificial intelligence deep learning has been
actively cross-combined with various fields to increase the effect of its original low single …

Wafer maps are extremely critical data that need to be carefully analyzed for quality control
and yield improvement. A wafer bin map (WBM) presents the chip probing test results for a …

It is not so easy to obtain the complete fault data for mechanical equipment toward certain
variable working conditions. Traditional deep learning algorithms based on limited training …

Big data analysis of wafer maps in semiconductor manufacturing is essential for process
reliability assessment, it is an important means of fault diagnosis in manufacturing. Although …

Deep neural networks require specific layers to process point clouds, as the scattered and
irregular location of 3D points prevents the use of conventional convolutional filters. We …

Defect pattern classification of wafer bin maps (WBMs) assists in identifying the causes of
semiconductor manufacturing process failures, thus contributing to the search for …

Concerning the problem that wafer surface defects are easily confused with the background
and are difficult to detect, a new detection method for wafer surface defects based on …

Wafer bin maps (WBMs) are essential test data in semiconductor manufacturing. WBM
defect classification can provide critical information for the improvement of manufacturing …

Inspecting defects in liquid-crystal display (LCD) manufacturing is of uttermost importance to
ensure customer's satisfaction and reduce time and money losses. Deep learning …